Latent deformation models for multivariate functional data and time-warping separability.

ABSTRACT: Multivariate functional data present theoretical and practical complications that are not found in univariate functional data. One of these is a situation where the component functions of multivariate functional data are positive and are subject to mutual time warping. That is, the component processes exhibit a common shape but are subject to systematic phase variation across their domains in addition to subject-specific time warping, where each subject has its own internal clock. This motivates a novel model for multivariate functional data that connect such mutual time warping to a latent-deformation-based framework by exploiting a novel time-warping separability assumption. This separability assumption allows for meaningful interpretation and dimension reduction. The resulting latent de

SUBMITTER: Carroll C 

PROVIDER: S-EPMC10480349 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature